For touch location estimation, some touch algorithm may treat capacitive panel measurements as point mass of a two dimensional (2D) touch “probe,” and apply a center of mass estimation (centroid) to find the location of the touching probe. For shape estimation, some processes treat the capacitive touch panel measurements as pixel values. The center of mass computation can be sub-optimal and subject to aliasing, which may cause bias and high jitter. For shape accuracy, a low pixel density makes it very difficult, if not impossible, to obtain accurate shape parameters, for example, angle of rotation and area. Accordingly, improvements and optimization in touch processing are desired.